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• W2207957129 abstract "The crop water footprint (WF) indicates the consumption of water for a crop during the planting period, mainly through evapotranspiration. However, as irrigated agriculture accounts for nearly 25% of the global agriculture water usage, evaluation of WF during transportation becomes essential to improve the efficiency of irrigated agriculture. This study aims at building an improved WF model to understand how much WF is produced due to water diversion and how much crop WF increases during the transfer. The proposed model is then used to calculate the WF of four major crops in five provinces along China's South-North Water Transfer Project in two steps. First, the WF of the water transfer project (WFeng) is assessed in a supply chain analysis method. Second, a WF allocation model is built to distribute the project WF for each crop/province. The results show that the evaporation and seepage are the main sources of WFeng. Out of five provinces, two namely Tianjin and Hebei present higher WFblue and WF increase. A positive correlation between water diversion distance and crop WF increase is noted. Among the four crops, cotton presents higher WFblue and WF increase. The crops with higher WFblue tend to be more strongly influenced by the water diversion project, due to high irrigation water dependency. This analysis may expand the WF concept from an evaporation-related term to a term reflecting crop biological processes and water consumption by artificial irrigation projects. Thus, it may serve as an indicator for optimizing future objectives and strategies associated to water resource planning in China and elsewhere." @default.
• W2207957129 created "2016-06-24" @default.
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• W2207957129 date "2016-03-01" @default.
• W2207957129 modified "2023-10-06" @default.
• W2207957129 title "Incorporating water consumption into crop water footprint: A case study of China's South–North Water Diversion Project" @default.
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• W2207957129 doi "https://doi.org/10.1016/j.scitotenv.2015.12.062" @default.
• W2207957129 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/26760279" @default.
• W2207957129 hasPublicationYear "2016" @default.
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